Spatial goals are becoming more frequent aspects of forest management plans as regulatory and organizational policies change in response to fi sheries and wildlife concerns. The combination of green-up constraints (harvesting restrictions that prevent the cutting of adjacent units for a specifi ed period of time) and habitat requirements for red-cockaded woodpeckers (RCW) in the southeastern U.S. suggests that spatially feasible forest plans be developed to guide management activities. We examined two modeling approaches aimed at developing management plans that had both harvest volume goals, RCW habitat, and green-up constraints. The fi rst was a two-stage method that in one stage used linear programming to assign volume goals, and in a second stage used a tabu search – genetic algorithm heuristic technique to minimize the deviations from the volume goals while maximizing the present net revenue and addressing the RCW and green-up constraints. The second approach was a one-stage procedure where the entire management plan was developed with the tabu search – genetic algorithm heuristic technique, thus it did not use the guidance for timber volume levels provided by the LP solution. The goal was to test two modeling approaches to solving a realistic spatial harvest scheduling problem. One is where to volume goals are calculated prior to developing the spatially feasible forest plan, while the other approach simultaneously addresses the volume goals while developing the spatially feasible forest plan. The resulting forest plan from the two-stage approach was superior to that produced from the one-stage approach in terms of net present value. The main point from this analysis is that heuristic techniques may benefi t from guidance provided by relaxed LP solutions in their effort to develop effi cient forest management plans, particularly when both commodity production and complex spatial wildlife habitat goals are considered. Differences in the production of forest products were apparent between the two modeling approaches, which could have a signifi cant effect on the selection of wood processing equipment and facilities.
Development of spatially feasible forest plans: a comparison of two modeling approaches
Published 2001 in Silva Fennica
ABSTRACT
PUBLICATION RECORD
- Publication year
2001
- Venue
Silva Fennica
- Publication date
Unknown publication date
- Fields of study
Computer Science, Environmental Science
- Identifiers
- External record
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Semantic Scholar
CITATION MAP
EXTRACTION MAP
CLAIMS
CONCEPTS
- green-up constraints
Harvest timing restrictions that prevent adjacent units from being cut within a specified period.
Aliases: green-up
- linear programming solution
The relaxed linear-programming output used to assign timber volume goals before spatial planning.
Aliases: LP solution
- net present value
The discounted economic metric used to compare candidate forest management plans.
Aliases: NPV
- one-stage procedure
A planning workflow that applies the heuristic directly to develop the forest plan without prior linear-programming guidance.
Aliases: one-stage approach, one-stage model
- red-cockaded woodpecker habitat requirements
Habitat-related spatial requirements for managing red-cockaded woodpecker habitat in southeastern U.S. forests.
Aliases: RCW habitat requirements, RCW habitat
- tabu search-genetic algorithm heuristic
A combined metaheuristic used to search for forest plans under volume, habitat, and spatial constraints.
Aliases: tabu search–genetic algorithm heuristic technique, tabu search genetic algorithm heuristic
- two-stage approach
A planning workflow that first uses linear programming to set volume goals and then applies a heuristic to build the final forest plan.
Aliases: two-stage method, two-stage model
- wood processing equipment and facilities
Downstream mill and facility choices that may depend on the mix of forest products produced by a plan.
Aliases: wood processing facilities
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